class_docstr: Class for the vector space of Hermitian matrices of size n.
  
  Parameters
  ----------
  n : int
      Integer representing the shapes of the matrices: n x n.
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docstr: Sample a Hermitian matrix.
  
  Points are generated by sampling complex matrices from a uniform distribution
  in a box and averaging with the transconjugate.
  
  Parameters
  ----------
  n_samples : int
      Number of samples.
      Optional, default: 1.
  bound : float
      Side of hypercube support of the uniform distribution.
      Optional, default: 1.0
  
  Returns
  -------
  point : array-like, shape=[..., n, n]
     Sample.
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code: def random_point(self, n_samples=1, bound=1.0):
      """Sample a Hermitian matrix.
  
      Points are generated by sampling complex matrices from a uniform distribution
      in a box and averaging with the transconjugate.
  
      Parameters
      ----------
      n_samples : int
          Number of samples.
          Optional, default: 1.
      bound : float
          Side of hypercube support of the uniform distribution.
          Optional, default: 1.0
  
      Returns
      -------
      point : array-like, shape=[..., n, n]
         Sample.
      """
      cdtype = gs.get_default_cdtype()
      size = self.shape
      if n_samples != 1:
          size = (n_samples,) + self.shape
      point = gs.cast(
          bound * (gs.random.rand(*size) - 0.5) * 2**0.5,
          dtype=cdtype,
      ) + 1j * gs.cast(
          bound * (gs.random.rand(*size) - 0.5) * 2**0.5,
          dtype=cdtype,
      )
      return ComplexMatrices.to_hermitian(point)
  
file_path: geomstats/geomstats/geometry/hermitian_matrices.py
imports: import logging
  import geomstats.backend
  from geomstats import algebra_utils
  from geomstats.geometry.base import ComplexMatrixVectorSpace
  from geomstats.geometry.complex_matrices import ComplexMatrices, ComplexMatricesMetric
  from geomstats.geometry.matrices import Matrices
label_desc: Use image node_id 6 for calling the HermitianMatrices obj's underlying member method code with example usage: obj.random_point(n_samples, bound) and returns: ComplexMatrices